Development of a Prognostic Model Based on Four Genes Related to Exhausted CD8+ T Cell in Triple-negative Breast Cancer Patients: a Comprehensive Analysis Integrating ScRNA-seq and Bulk RNA-seq

Overview

Journal Discov Oncol

Publisher Springer

Date 2025 Feb 3

PMID 39899181

Authors

Yulin Shi

Yang Yu

Jiahan Zhao

Linan Huang

Qingyang Wang

Qi Sun

Lijuan Liu

Changgang Sun

Affiliations

Soon will be listed here.

Abstract

Low immune infiltration is closely associated with poor clinical results and an unfavorable response to therapy in triple-negative breast cancer (TNBC). T-cell exhaustion (TEX) is a significant risk factor for tumor immunosuppression and invasion. Although improving TEX and enhancing effector function are promising strategies for strengthening immunotherapy, their role in the pathogenesis of TNBC remains unclear. This study's objective was to develop a prognostic model for TNBC based on exhausted CD8+ T-cell (CD8+ Tex)-related differentially expressed genes (DEGs) and to investigate its clinical and immune relevance. Initially, 398 CD8+ Tex-related genes were screened utilizing single-cell RNA sequencing (scRNA-seq) data from TNBC patients. Pseudotime analysis confirmed that CD8+ Tex mainly clustered at the end of the differentiation pathways, making them a critical subset in TNBC progression. By analyzing the TCGA cohort, ten CD8+ Tex-related DEGs were identified as significantly correlated with overall survival (OS) in TNBC patients, and a prognostic model containing four biomarkers (GBP1, CTSD, ABHD14B, and HLA-A) was constructed. The model demonstrated robust predictive capability in both the TCGA cohort and an external cohort, with the low-risk group exhibiting elevated expression of immunological checkpoint molecules and immune cell infiltration, as well as better responses to immunotherapy and chemotherapy. Furthermore, these four biomarkers were found to be highly expressed on CD8+ Tex and were associated with cellular communication efficiency. Therefore, this model is expected to be a new method for forecasting TNBC patients' prognosis and effectiveness of treatment, providing new insights for clinical decision-making.

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